{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f4231c63",
   "metadata": {},
   "source": [
    "# MaixPy3 基本使用示例"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "82e6fe35",
   "metadata": {},
   "source": [
    "| 时间 | 负责人 | 更新内容 | 备注 |\n",
    "| --- | --- | --- | --- |\n",
    "| 2022年1月18日 | dianjixz | 编写文档初稿 | 使用 jupyter notebook 编写，可以直接运行 |\n",
    "\n",
    "假设你会 python ，并具有基础的视觉知识，下面是 maixpy3 的最简程序示例。\n",
    "\n",
    "\n",
    "## \"hello world!\"\n",
    "\n",
    "确保目标机器已经安装 maixpy3 软件包。\n",
    "\n",
    "使用 maixpy3 包在图像上显示 \"hello world!\" 。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ae04d801",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ rpyc-kernel ]( running at Fri Jan 14 16:48:03 2022 )\n"
     ]
    }
   ],
   "source": [
    "from maix import display, image   #引入python模块包\n",
    "\n",
    "hello_img = image.Image().new(size = (240, 240), \n",
    "                              color = (255, 0, 0), mode = \"RGB\")     #创建一张红色背景图\n",
    "\n",
    "hello_img.draw_string(30, 115, \"hello world!\", scale = 1.0, \n",
    "                              color = (255, 255, 255), thickness = 1) #在红色背景图上写下hello world\n",
    "\n",
    "display.show(hello_img)   #把这张图显示出来"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76ba5402",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "## 从摄像头获取图像并显示\n",
    "\n",
    "使用 maixpy3 包从摄像头获取图像并显示。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a7d8673e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "\r\n",
       "Traceback (most recent call last):\r\n",
       "  File \"<string>\", line unknown, in <module>\r\n",
       "Remote.KeyboardInterrupt\r\n"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from maix import camera, display, image #引入python模块包\n",
    "\n",
    "while True:\n",
    "    img = camera.capture()    #从摄像头中获取一张图像\n",
    "    display.show(img)         #将图像显示出来"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7001105f",
   "metadata": {},
   "source": [
    "\n",
    "## 图像的基础操作\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 图像的画线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "30e0b142",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ rpyc-kernel ]( running at Fri Jan 14 16:47:26 2022 )\n"
     ]
    }
   ],
   "source": [
    "from maix import image, display\n",
    "\n",
    "img = image.Image().new(size = (240, 240), color = (0, 0, 0), \n",
    "                        mode = \"RGB\")     #创建一张黑色背景图\n",
    "\n",
    "img.draw_line(0, 0, 100, 100, color = (127, 127, 127), \n",
    "                        thickness = 1)  #画一条从（0,0）到（100,100）的白色线段\n",
    "\n",
    "display.show(img)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3bad6497",
   "metadata": {},
   "source": [
    "### 图像的画框"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "46a92c4e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ rpyc-kernel ]( running at Fri Jan 14 16:41:39 2022 )\n"
     ]
    }
   ],
   "source": [
    "from maix import image, display\n",
    "\n",
    "img = image.Image().new(size = (240, 240), color = (0, 0, 0), \n",
    "                        mode = \"RGB\")     #创建一张黑色背景图\n",
    "\n",
    "img.draw_rectangle(80, 160, 160, 200, color=(0, 0, 255), \n",
    "                       thickness=1)   #画一个从（80, 160）到（160, 200）的蓝色矩形外框\n",
    "\n",
    "img.draw_rectangle(10, 10, 60, 60, color=(255, 0, 0), \n",
    "                       thickness=-1)   #画一个从（80, 160）到（160, 200）的红色实心矩形\n",
    "\n",
    "display.show(img)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d36fa2f2",
   "metadata": {},
   "source": [
    "### 图像的画圆"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "16b74e3c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ rpyc-kernel ]( running at Fri Jan 14 16:45:05 2022 )\n"
     ]
    }
   ],
   "source": [
    "from maix import image, display\n",
    "\n",
    "img = image.Image().new(size = (240, 240), color = (0, 0, 0), \n",
    "                        mode = \"RGB\")     #创建一张黑色背景图\n",
    "\n",
    "img.draw_circle(50, 50, 20, color=(0, 0, 255), \n",
    "                        thickness=1)   #画一个中心点在（50,50），半径为20的空心蓝圆\n",
    "\n",
    "img.draw_circle(150, 150, 20, color=(255, 0, 0), \n",
    "                        thickness=-1)  #画一个中心点在（150,150），半径为20的实心红圆\n",
    "\n",
    "display.show(img)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f12af35b",
   "metadata": {},
   "source": [
    "### 图像的画字符\n",
    "\n",
    "注意：显示中文时需要加载字库！"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0b0148ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ rpyc-kernel ]( running at Fri Jan 14 16:49:17 2022 )\n"
     ]
    }
   ],
   "source": [
    "from maix import display, image   #引入python模块包\n",
    "\n",
    "hello_img = image.Image().new(size = (240, 240), color = (0, 0, 0), \n",
    "                              mode = \"RGB\")     #创建一张黑色背景图\n",
    "\n",
    "hello_img.draw_string(30, 115, \"hello world!\", scale = 1.0, color = (255, 255, 255), \n",
    "                              thickness = 1) #在黑色背景图上写下hello world\n",
    "\n",
    "display.show(hello_img)   #把这张图显示出来"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f093553e",
   "metadata": {},
   "source": [
    "### 图像的画椭圆"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "eb2cf1aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ rpyc-kernel ]( running at Fri Jan 14 16:49:49 2022 )\n"
     ]
    }
   ],
   "source": [
    "from maix import image, display\n",
    "\n",
    "img = image.Image().new(size = (240, 240), color = (0, 0, 0), \n",
    "                        mode = \"RGB\")     #创建一张黑色背景图\n",
    "\n",
    "img.draw_ellipse(120, 40, 20, 50, 90, 0, 360, color=(0,255,0), \n",
    "                        thickness = 1)\n",
    "\n",
    "display.show(img)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9aed0ce4",
   "metadata": {},
   "source": [
    "画椭圆的参数比较复杂，详情请查看 miaxpy3 API 。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90ce1387",
   "metadata": {},
   "source": [
    "### 图像的打开与保存"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d8b52d1c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from maix import image, display\n",
    "\n",
    "img = image.Image()\n",
    "\n",
    "img.new(size=(240, 240), mode=\"RGB\")\n",
    "img.draw_line(0, 0, 240, 240)\n",
    "img.draw_rectangle(40, 120, 160, 200, color=(255, 0, 0), thickness=16)\n",
    "img.draw_circle(120, 120, 20, color=(0, 255, 0))\n",
    "img.draw_string(40, 40, \"dalaoshu\", 2, color=(0, 0, 255))\n",
    "\n",
    "img.save(\"/root/test.png\")\n",
    "\n",
    "tmp = image.Image()\n",
    "tmp.open(\"/root/test.png\")\n",
    "\n",
    "display.show(tmp)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e48e578d",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "## vision 算法\n",
    "\n",
    "maixpy3 中集成了一些常用的 vision 算法，下面是 vision 算法的简单使用例子。\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d7e37e94",
   "metadata": {},
   "source": [
    "### 寻找色块\n",
    "\n",
    "使用 maixpy3 的查找色块算法，查找图像中符合颜色阈值的色块。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9220f2c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "\r\n",
       "Traceback (most recent call last):\r\n",
       "  File \"<string>\", line unknown, in <module>\r\n",
       "Remote.KeyboardInterrupt\r\n"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from maix import image, display, camera    #导入需要的包\n",
    "\n",
    "bull = [(13, 11, -91, 54, 48, -28)]  # 蓝色的lab阈值\n",
    "\n",
    "while True:\n",
    "    img = camera.capture()       #获取一张图片\n",
    "    \n",
    "    blobs = img.find_blobs(bull)    #在图片中查找lab阈值内的颜色色块\n",
    "    \n",
    "    if blobs:             #判断是否找到颜色\n",
    "        for i in blobs:   #遍历颜色\n",
    "            img.draw_rectangle(i[\"x\"], i[\"y\"], i[\"x\"] + i[\"w\"], i[\"y\"] + i[\"h\"], \n",
    "                               color=(0, 0, 255), thickness=1) #将找到的颜色区域画出来\n",
    "            \n",
    "    display.show(img)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8ec1490",
   "metadata": {},
   "source": [
    "### 视觉找线\n",
    "\n",
    "找线算法是面对小车寻线而开发的一个算法。主要的流程是，灰度化 -> 自适应阈值处理 -> 形态学运算 -> 图像最小二乘法。完成算法流程后返回一条线的信息，让小车能够根据识别出来线的信息进行运动。这个接口比较适合做图像寻线。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d3306f13",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "\r\n",
       "Traceback (most recent call last):\r\n",
       "  File \"<string>\", line unknown, in <module>\r\n",
       "Remote.KeyboardInterrupt\r\n"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from maix import image, display, camera\n",
    "import time\n",
    "\n",
    "while True:\n",
    "  img = camera.capture()\n",
    "  line = img.find_line()\n",
    "  img.draw_line(line[\"rect\"][0], line[\"rect\"][1], line[\"rect\"][2],\n",
    "                line[\"rect\"][3], color=(255, 255, 255), thickness=1)\n",
    "  img.draw_line(line[\"rect\"][2], line[\"rect\"][3], line[\"rect\"][4],\n",
    "                line[\"rect\"][5], color=(255, 255, 255), thickness=1)\n",
    "  img.draw_line(line[\"rect\"][4], line[\"rect\"][5], line[\"rect\"][6],\n",
    "                line[\"rect\"][7], color=(255, 255, 255), thickness=1)\n",
    "  img.draw_line(line[\"rect\"][6], line[\"rect\"][7], line[\"rect\"][0],\n",
    "                line[\"rect\"][1], color=(255, 255, 255), thickness=1)\n",
    "  img.draw_circle(line[\"cx\"], line[\"cy\"], 4,\n",
    "                  color=(255, 255, 255), thickness=1)\n",
    "  display.show(img)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c5746ef",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "### 获取区域的颜色\n",
    "\n",
    "颜色统计算法，统计感兴趣区域最多的颜色并返回。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "09c23d85",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "\r\n",
       "Traceback (most recent call last):\r\n",
       "  File \"<string>\", line unknown, in <module>\r\n",
       "Remote.KeyboardInterrupt\r\n"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from maix import image, display, camera\n",
    "import time\n",
    "\n",
    "while True:\n",
    "  img = camera.capture()\n",
    "  colors = img.get_blob_color((100, 100, 10, 10), 0, 0)\n",
    "  img.draw_rectangle(100, 100, 110, 110, \n",
    "                               color=(255, 0, 0), thickness=1) #将找到的颜色区域画出来\n",
    "  img.draw_rectangle(9, 9, 21, 21, \n",
    "                               color=(255, 255, 255), thickness=1) #将找到的颜色区域画出来\n",
    "  img.draw_rectangle(10, 10, 20, 20, \n",
    "                               color=(int(colors[0]), int(colors[1]), int(colors[2])), thickness=-1) #将找到的颜色区域画出来\n",
    "  display.show(img)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6d5ca8c",
   "metadata": {},
   "source": [
    "   \n",
    "### 识别二维码 \n",
    "\n",
    "采用 zbar 实现，查找画面中出现的二维码。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "03c41e0c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "\r\n",
       "Traceback (most recent call last):\r\n",
       "  File \"<string>\", line unknown, in <module>\r\n",
       "Remote.KeyboardInterrupt\r\n"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from maix import camera, display, zbar\n",
    "while True:\n",
    "    img = camera.capture()\n",
    "    result = zbar.scan_codes([\"qrcode\", \"code39\"], img)\n",
    "    display.show(tmp.draw_string(10, 10, str(result), 2.0, (255, 0, 0)))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e15217f",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "## 更多传统视觉方法小编正在努力开发中，敬请期待！！！"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "RPyc-Python",
   "language": "Python",
   "name": "rpyc"
  },
  "language_info": {
   "codemirror_mode": "python",
   "file_extension": ".py",
   "mimetype": "text/python",
   "name": "Python"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
